In the framework of laser imaging, a Ladar (Laser Radar) illuminates a scene 1 containing an object 10 which is partially camouflaged by any obstacle (trees in the figure) allowing part of the laser wave to pass as illustrated in FIG. 1. The wave is thus retro-reflected by the object 10 and the signal is analysed by the Ladar system. Various positions of the Ladar allow a 3D image to be reconstructed.
In the framework of passive imaging, a 3D image is reconstructed by using the reflections of external sources (sun, moon, background sky, etc.) on the object and/or the object's own thermal emission.
In this field of 3D imaging (passive or active), a set of measurements must be obtained relating to the object to be reconstructed depending on a variable angular observation parameter, this set of data allowing the volume to be reconstructed by applying techniques of inverse reconstruction. From a mathematical point of view, the technique makes use of a direct measurement. The inverse model is then used to restore the three-dimensional nature of the object, using the results of the direct measurement.
When the imaging system forms images of a scene containing an object partially camouflaged by trees, or by any other obstacle, the creation of a 3D image of an object present in a complex optronic scene is incomplete or missing parts.
There are two major types of 3D Ladar imaging, reflection tomography and profilometry.
Tomography uses two-dimensional laser images depending on a variable angle: the reconstruction of the totality of the scene common to all of the images of the sequence is carried out by a technique of the Radon transformation type.
Profilometry based on measurements of the time-of-flight of a laser wave uses the positions of various points of back-scattering from the objects of the scene classified in a three-dimensional space thanks to the determination of the time-of-flight of the laser wave and to the knowledge of the positioning of the laser beam. These profilometry systems use short pulses (of the order of a nanosecond) in order to discriminate the various echos over the same target line. This then generates a profile of the echos over the target line.
Wideband detectors can be used in order to reproduce the profile of the echo. Thus, for the 1.5 μm band, there are InGaAs detectors of the PIN type (P layer—Intrinsic layer—N layer) or of the APD (Avalanche PhotoDiode) type. A set of clusters of points corresponding to several positions of the system then just need to be concatenated. It is often necessary to process all of the data in order to compensate for the error in localization of the system. The method may be completed by a scan of the detection system and of the laser beam.
Another technique uses techniques for ‘gating’ the detector allowing sections of clusters of points to be reconstituted by means of a high-pulse-rate laser. The scene is then illuminated by a group of laser pulses whose back-scattering is collected according to the various depths of the objects in the scene, by a matrix of pixels having a precise time window or ‘gate’ of a few hundreds of picoseconds. The image is then obtained with a dimension linked to the depth. In order to obtain a 3D image, various viewing angles are needed.
In the various scenarios considered (sensors carried by a UAV, for Unmanned Aerial Vehicle, a helicopter or an aeroplane), the reconstruction is often incomplete when the object is camouflaged, the signals back-scattered by the object no longer allowing all of the information associated with the object to be obtained. This then results in incomplete and missing information leading to a process of partial inversion delivering an incomplete 3D image. The process of concatenation of clusters of points is considered as a process of inversion. One example of a process of partial inversion is shown in FIG. 2, for which the three-dimensional image is incomplete, and where the regions requiring a completion of data can be identified.
The techniques normally used to complete the three-dimensional image make use of a pre-existing database, a CAD database for example. The object reconstructed is then compared with elements of this database. If a correlation with the initial 3D object is obtained, the three-dimensional image is completed with the data, textured or otherwise, from the database. These completion algorithms depend on the richness of the CAD models in the database, which presents the huge drawback of not being usable if the object is unknown in this database.